Must-Have
- 5+ years of professional experience as a Data Analyst with good decision-making, analytical and problem-solving skills.
- SQL, Pyspark, Python with Banking Domain knowledge - Credit & Lending.
Working knowledge / experience of Big Data frameworks like Hadoop, Hive and Spark.
- Hands-on experience in query languages like HQL or SQL (Spark SQL) for Data exploration.
- Data mapping: Determine the data mapping required to join multiple data sets together across multiple sources.
- Documentation - Data Mapping, Subsystem Design, Technical Design, Business Requirements.
- Exposure to Logical to Physical Mapping, Data Processing Flow to measure the consistency, etc.
- Data Asset design / build: Working with the data model / asset generation team to identify critical data elements and determine the mapping for reusable data assets.
- Understanding of ER Diagram and Data Modelling concepts
- Exposure to Data quality validation
- Exposure to Data Management, Data Cleaning and Data Preparation
- Exposure to Data Schema analysis.
- Exposure to working in Agile framework.
- Knowledge of Credit Risk Frameworks such as Basel II, III, IFRS 9 and Stress Testing and understanding their drivers - advantageous
